The science community’s bad bet left us unprepared for the coronavirus.

Why the bad bet?
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In a prior post, we channeled a report titled “The Road Not Traveled” by investigative reporter Christine Dolan.

For details, see: 15 years ago, scientists bet that the next pandemic would NOT be a coronavirus …

In a nutshell, Dolan concludes that circa 2003:

The scientific world bet that the next big pandemic would emanate from a more traditional flu and not a coronavirus like Sudden Acute Respiratory Syndrome (SARS) or Middle East Respiratory Syndrome (MERS).

Obviously, that bet proved wrong … deadly wrong!

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How did the science community collectively miss the mark?

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According to Dolan’ report

Retrospectively, experts say the decision to prioritize a pandemic flu over the coronavirus was based on risk assumptions.

Pandemic Flu was expected to spread much faster and become more lethal because of the natural spread by birds across continents and via significant human travel by air (of which the models predicted it to kill millions quickly).

COVID-19 does not spread across continents by natural spread via birds but only via human to human contact, which we would expect to be more easily containable.”

“We knew a pandemic was coming at some point. But, given our experiences with SARS1, MERS (whose extent was relatively small and short-lived) versus the various flu epidemics, it was not unreasonable to put our bets on flu”.

That may be true and offers a reasonable rationale, but…

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Let me offer a compounding hypothesis …

One of the courses I taught centered on how to solve complex problems.

The starting point was asking the right question and solving the right problem.

I always pointed to research done by the enter for Creative Leadership that concluded:

“Managers faced with a complex problem typically end up solving the wrong problem.”

Why is that?

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I offered up 5 common reasons or “stumbling blocks” to identifying the right problem:

  1. Wandering into new territory, i.e dealing with a situation that doesn’t fit existing paradigms
  2. “Noise” obscures the “signal”, i.e. given a myriad of complicating (and sometimes conflicting) data and observations, it isn’t clear which is the most important
  3. Fixation hides periphery and nuances, i.e. seizing on an apparently likely suspect without considering other possible alternatives.
  4. Unconscious biases take over, i.e. tending to ignore information that is inconsistent with the current “world view”
  5. Preference for simpler problems, i.e. staying within a comfort zone of most likely solvable questions.

My hunch: the scientists who bet against the likelihood of a coronavirus pandemic were well-intended but stumbled on some (or all) of the above blocks:

  1. “Novel” coronavirus signals that it doesn’t fit existing paradigms
  2. Pandemics have scientific, economic and political consequences that interact
  3. Globalization (e.g. air travel) hastens the human to human viral spread.
  4. Public health experts focus on, well, public health … minimizing, say, economic consequences
  5. Obviously, the coronavirus is a hard nut to crack scientifically … so, human nature drifts to problems that might be easier to solve.

Regarding the last point, it’s apparent that scientists are still scrambling to:

  • Understand the covid-19 coronavirus
  • Deploy fast and accurate diagnostic tests
  • Calibrate the virus’ susceptibility, potency and magnitude
  • Establish effective treatment protocols
  • Speed development of therapeutic drugs and vaccines.

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Regardless of the reasons “why” the bad bet was placed, the bottom line is that the majority of the global preparation before now was centered on pandemic flu not coronaviruses.

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Next up: The implications

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